Hierarchichal sharding of flows from sensors to collectors

ABSTRACT

Systems, methods, and computer-readable media for hierarchichal sharding of flows from sensors to collectors. A first collector can receive a first portion of a network flow from a first capturing agent and determine that a second portion of the network flow was not received from the first capturing agent. The first collector can then send the first portion of the network flow to a second collector. A third collector can receive the second portion of the network flow from a second capturing agent and determine that the third collector did not receive the first portion of the network flow. The third collector can then send the second portion of the network flow to the second collector. The second collector can then aggregate the first portion and second portion of the network flow to yield the entire portion of the network flow.

CROSS-REFERENCE TO RELATED APPLICATIONS

The instant application is a Continuation of, and claims priority to,U.S. patent application Ser. No. 16/392,950 entitled HIERARCHICHALSHARDING OF FLOWS FROM SENSORS TO COLLECTORS filed Apr. 24, 2019, whichis a Continuation of, and claims priority to, U.S. patent applicationSer. No. 15/171,855 entitled HIERARCHICHAL SHARDING OF FLOWS FROMSENSORS TO COLLECTORS filed Jun. 2, 2016, which is priority to, U.S.Patent Application No. 62/171,899 entitled SYSTEM FOR MONITORING ANDMANAGING DATACENTERS filed Jun. 5, 2015, the contents of which areherein incorporated by reference in their entireties.

TECHNICAL FIELD

The present disclosure pertains to network analytics, and morespecifically to capturing network flows in the network, and sharding orgrouping the network flows for scalability of the captured networkflows.

BACKGROUND

In a network environment, capturing agents or sensors can be placed atvarious devices or elements in the network to collect flow data andnetwork statistics from different locations. The collected data from thecapturing agents can be analyzed to monitor and troubleshoot thenetwork. The data collected from the capturing agents can providevaluable details about the status, security, or performance of thenetwork, as well as any network elements. Information about thecapturing agents can also help interpret the data from the capturingagents, in order to infer or ascertain additional details from thecollected data. For example, understanding the placement (e.g.,deployment location) of a capturing agent within a device or virtualizedenvironment can provide a context to the data reported by the capturingagents, which can further help identify specific patterns or conditionsin the network.

With larger networks, however, the number of capturing agents andsessions can grow to millions or more. It thus becomes very difficult toscale the numerous capturing agents and sensors. Moreover, as the numberof collectors used in the network to collect the captured data from thecapturing agents grows, it becomes increasingly difficult to track,organize, and maintain different portions of the same network flow.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are nottherefore to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIG. 1 illustrates a diagram of an example network environment;

FIG. 2A illustrates a schematic diagram of an example capturing agentdeployment in a virtualized environment;

FIG. 2B illustrates a schematic diagram of an example capturing agentdeployment in an example network device;

FIG. 2C illustrates a schematic diagram of an example reporting systemin an example capturing agent topology;

FIG. 3 illustrates a schematic diagram of an example configuration forcollecting capturing agent reports;

FIG. 4A illustrates a schematic diagram of a multi-layer shardingscheme;

FIG. 4B illustrates a schematic diagram of a system for hierarchicalsharding collectors, sensors, and flows in accordance with variousexample embodiments;

FIG. 5 illustrates an example listing of example fields on a capturingagent report;

FIG. 6 illustrates an example method;

FIG. 7 illustrates an example network device; and

FIGS. 8A and 8B illustrate example systems.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Various examples of the disclosure are discussed in detail below. Whilespecific implementations are discussed, it should be understood thatthis is done for illustration purposes only. A person skilled in therelevant art will recognize that other components and configurations maybe used without parting from the spirit and scope of the disclosure. Anystep or component of one example or embodiment disclosed herein can beused or combined with any other example or embodiment.

OVERVIEW

Additional features and advantages of the disclosure will be set forthin the description which follows, and in part will be obvious from thedescription, or can be learned by practice of the herein disclosedprinciples. The features and advantages of the disclosure can berealized and obtained by means of the instruments and combinationsparticularly pointed out in the appended claims. These and otherfeatures of the disclosure will become more fully apparent from thefollowing description and appended claims, or can be learned by thepractice of the principles set forth herein.

The approaches set forth herein can be used to improve the management,collection, and aggregation of analytics data in a network. Theapproaches herein can ensure that different portions of a network floware aggregated and/or maintained together even when reported bycapturing agents to different collectors in the network. The approachesherein can use a first layer of shards, which can include groups ofcollectors, to scale the collectors and sensed data. The approachesherein can also use a second layer of shards, which can also includegroups of collectors, to maintain, in a centralized location (e.g., acollector in the second layer of shards), all of the different portionsof a network flow reported to collectors in the first layer of shards.This multi-layered or hierarchical sharding approach can help moreeffectively and efficiently manage the collection and aggregation ofanalytics data in a network, while also centralizing fragmented portionsof reported data to enable defragmentation of all reported portions ofthe data.

Disclosed are systems, methods, and computer-readable storage media forhierarchichal sharding of network flows reported from capturing agentsdeployed around a network. In an example method, collectors in a networkcan be grouped into a first layer of shards, and each shard can includea set of collectors. A second layer of shards can also be created bymapping groups of collectors to respective shards in the second layer ofshards.

Moreover, a first collector in a first shard from the first layer ofshards can receive, from a first capturing agent, a first portion of anetwork flow. The first portion of the network flow can be captured bythe first capturing agent at the first capturing agent's host, such as ahypervisor, virtual machine (VM), server, switch, etc.

The first collector can then determine that a second portion of thenetwork flow was not received by the first collector. For example, thefirst collector can determine that it did not receive the entire networkflow (e.g., at least a portion of the network flow is missing). Thefirst collector can then send the first portion of the network flow to asecond collector from a second shard in a second layer of shards.

A third collector from a third shard in the first layer of shards canreceive, from a second capturing agent, the second portion of thenetwork flow. The second portion can be captured by the second capturingagent at a host of the second capturing agent, such as a hypervisor, aVM, a container, a server, etc. The third collector can determine thatthe first portion of the network flow was not received by the thirdcollector. In other words, the third collector can determine that itreceived less than the entire network flow.

The third collector can then send, to the second collector, the secondportion of the network flow. The third collector can send the secondportion based on the determination that it did not receive the firstportion of the network flow.

The second collector can receive the first portion from the firstcollector and the second portion from the third collector. The secondcollector can then determine that the first portion and the secondportion are part of the same network flow. Accordingly, the secondcollector can then aggregate the first portion and the second portion toyield an aggregated network flow. The aggregated network flow caninclude the entire portion of the network flow. However, in some cases,if other portions of the network flow were sent by other capturingagents to other collectors, those receiving collectors can similarlysend their received portions to the second collector so that the secondcollector can aggregate all portions of the network flow.

DESCRIPTION

The disclosed technology addresses the need in the art for scaling thecapturing and collection of network data. Disclosed are systems,methods, and computer-readable storage media for hierarchichal shardingof network flows in a network. A description of an example networkenvironment, as illustrated in FIG. 1, is first disclosed herein. Adiscussion of capturing agents and collection environments andconfigurations will then follow. The discussion continues with adiscussion of hierarchichal sharding of network flows, sensors, andcollectors. The discussion then concludes with a description of examplesystems and devices. These variations shall be described herein as thevarious embodiments are set forth. The disclosure now turns to FIG. 1.

FIG. 1 illustrates a diagram of example network environment 100. Fabric112 can represent the underlay (i.e., physical network) of networkenvironment 100. Fabric 112 can include spine routers 1-N (102 _(A-N))(collectively “102”) and leaf routers 1-N (104 _(A-N)) (collectively“104”). Leaf routers 104 can reside at the edge of fabric 112, and canthus represent the physical network edges. Leaf routers 104 can be, forexample, top-of-rack (“ToR”) switches, aggregation switches, gateways,ingress and/or egress switches, provider edge devices, and/or any othertype of routing or switching device.

Leaf routers 104 can be responsible for routing and/or bridging tenantor endpoint packets and applying network policies. Spine routers 102 canperform switching and routing within fabric 112. Thus, networkconnectivity in fabric 112 can flow from spine routers 102 to leafrouters 104, and vice versa.

Leaf routers 104 can provide servers 1-4 (106 _(A-D)) (collectively“106”), hypervisors 1-4 (108 _(A)-108 _(D)) (collectively “108”),virtual machines (VMs) 1-4 (110 _(A)-110 _(D)) (collectively “110”),collectors 118, engines 120, and the Layer 2 (L2) network access tofabric 112. For example, leaf routers 104 can encapsulate anddecapsulate packets to and from servers 106 in order to enablecommunications throughout environment 100. Leaf routers 104 can alsoconnect other network-capable device(s) or network(s), such as afirewall, a database, a server, etc., to the fabric 112. Leaf routers104 can also provide any other servers, resources, endpoints, externalnetworks, VMs, services, tenants, or workloads with access to fabric112.

VMs 110 can be virtual machines hosted by hypervisors 108 running onservers 106. VMs 110 can include workloads running on a guest operatingsystem on a respective server. Hypervisors 108 can provide a layer ofsoftware, firmware, and/or hardware that creates and runs the VMs 110.Hypervisors 108 can allow VMs 110 to share hardware resources on servers106, and the hardware resources on servers 106 to appear as multiple,separate hardware platforms. Moreover, hypervisors 108 and servers 106can host one or more VMs 110. For example, server 106 _(A) andhypervisor 108 _(A) can host VMs 110 _(A-B).

In some cases, VMs 110 and/or hypervisors 108 can be migrated to otherservers 106. For example, VM 110 _(A) can be migrated to server 106 andhypervisor 108 _(B). Servers 106 can similarly be migrated to otherlocations in network environment 100. For example, a server connected toa specific leaf router can be changed to connect to a different oradditional leaf router. In some cases, some or all of servers 106,hypervisors 108, and/or VMs 110 can represent tenant space. Tenant spacecan include workloads, services, applications, devices, and/or resourcesthat are associated with one or more clients or subscribers.Accordingly, traffic in network environment 100 can be routed based onspecific tenant policies, spaces, agreements, configurations, etc.Moreover, addressing can vary between one or more tenants. In someconfigurations, tenant spaces can be divided into logical segmentsand/or networks and separated from logical segments and/or networksassociated with other tenants.

Any of leaf routers 104, servers 106, hypervisors 108, and VMs 110 caninclude capturing agent 116 (also referred to as a “sensor”) configuredto capture network data, and report any portion of the captured data tocollector 118. Capturing agents 116 can be processes, agents, modules,drivers, or components deployed on a respective system or system layer(e.g., a server, VM, virtual container, hypervisor, leaf router, etc.),configured to capture network data for the respective system (e.g., datareceived or transmitted by the respective system), and report some orall of the captured data and statistics to collector 118.

For example, a VM capturing agent can run as a process, kernel module,software element, or kernel driver on the guest operating systeminstalled in a VM and configured to capture and report data (e.g.,network and/or system data) processed (e.g., sent, received, generated,etc.) by the VM.

A hypervisor capturing agent can run as a process, kernel module,software element, or kernel driver on the host operating systeminstalled at the hypervisor layer and configured to capture and reportdata (e.g., network and/or system data) processed (e.g., sent, received,generated, etc.) by the hypervisor.

A container capturing agent can run as a process, kernel module,software element, or kernel driver on the operating system of a device,such as a switch or server, which can be configured to capture andreport data processed by the container.

A server capturing agent can run as a process, kernel module, softwareelement, or kernel driver on the host operating system of a server andconfigured to capture and report data (e.g., network and/or system data)processed (e.g., sent, received, generated, etc.) by the server.

A network device capturing agent can run as a process, software element,or component in a network device, such as leaf routers 104, andconfigured to capture and report data (e.g., network and/or system data)processed (e.g., sent, received, generated, etc.) by the network device.

Capturing agents 116 can be configured to report observed data,statistics, and/or metadata about one or more packets, flows,communications, processes, events, and/or activities to collector 118.For example, capturing agents 116 can capture network data andstatistics processed (e.g., sent, received, generated, dropped,forwarded, etc.) by the system or host (e.g., server, hypervisor, VM,container, switch, etc.) of the capturing agents 116 (e.g., where thecapturing agents 116 are deployed). The capturing agents 116 can alsoreport the network data and statistics to one or more devices, such ascollectors 118 and/or engines 120. For example, the capturing agents 116can report an amount of traffic processed by their host, a frequency ofthe traffic processed by their host, a type of traffic processed (e.g.,sent, received, generated, etc.) by their host, a source or destinationof the traffic processed by their host, a pattern in the traffic, anamount of traffic dropped or blocked by their host, types of requests ordata in the traffic received, discrepancies in traffic (e.g., spoofedaddresses, invalid addresses, hidden sender, etc.), protocols used incommunications, type or characteristics of responses to traffic by thehosts of the capturing agents 116, what processes have triggeredspecific packets, etc.

Capturing agents 116 can also capture and report information about thesystem or host of the capturing agents 116 (e.g., type of host, type ofenvironment, status of host, conditions of the host, etc.). Suchinformation can include, for example, data or metadata of active orpreviously active processes of the system, operating system useridentifiers, kernel modules loaded or used, network softwarecharacteristics (e.g., software switch, virtual network card, etc.),metadata of files on the system, system alerts, number and/or identityof applications at the host, domain information, networking information(e.g., address, topology, settings, connectivity, etc.), sessioninformation (e.g., session identifier), faults or errors, memory or CPUusage, threads, filename and/or path, services, security information orsettings, and so forth.

Capturing agents 116 may also analyze the processes running on therespective VMs, hypervisors, servers, or network devices to determinespecifically which process is responsible for a particular flow ofnetwork traffic. Similarly, capturing agents 116 may determine whichoperating system user (e.g., root, system, John Doe, Admin, etc.) isresponsible for a given flow. Reported data from capturing agents 116can provide details or statistics particular to one or more tenants orcustomers. For example, reported data from a subset of capturing agents116 deployed throughout devices or elements in a tenant space canprovide information about the performance, use, quality, events,processes, security status, characteristics, statistics, patterns,conditions, configurations, topology, and/or any other information forthe particular tenant space.

Collectors 118 can be one or more devices, modules, workloads, VMs,containers, and/or processes capable of receiving data from capturingagents 116. Collectors 118 can thus collect reports and data fromcapturing agents 116. Collectors 118 can be deployed anywhere in networkenvironment 100 and/or even on remote networks capable of communicatingwith network environment 100. For example, one or more collectors can bedeployed within fabric 112, on the L2 network, or on one or more of theservers 106, VMs 110, hypervisors. Collectors 118 can be hosted on aserver or a cluster of servers, for example. In some cases, collectors118 can be implemented in one or more servers in a distributed fashion.

As previously noted, collectors 118 can include one or more collectors.Moreover, a collector can be configured to receive reported data fromall capturing agents 116 or a subset of capturing agents 116. Forexample, a collector can be assigned to a subset of capturing agents 116so the data received by that specific collector is limited to data fromthe subset of capturing agents 116. Collectors 118 can be configured toaggregate data from all capturing agents 116 and/or a subset ofcapturing agents 116. Further, collectors 118 can be configured toanalyze some or all of the data reported by capturing agents 116.

Environment 100 can include one or more analytics engines 120 configuredto analyze the data reported to collectors 118. For example, engines 120can be configured to receive collected data from collectors 118,aggregate the data, analyze the data (individually and/or aggregated),generate reports, identify conditions, compute statistics, visualizereported data, troubleshoot conditions, visualize the network and/orportions of the network (e.g., a tenant space), generate alerts,identify patterns, calculate misconfigurations, identify errors,generate suggestions, generate testing, detect compromised elements(e.g., capturing agents 116, devices, servers, switches, etc.), and/orperform any other analytics functions.

Engines 120 can include one or more modules or software programs forperforming such analytics. Further, engines 120 can reside on one ormore servers, devices, VMs, nodes, etc. For example, engines 120 can beseparate VMs or servers, an individual VM or server, or a cluster ofservers or applications. Engines 120 can reside within the fabric 112,within the L2 network, outside of the environment 100 (e.g., WAN 114),in one or more segments or networks coupled with the fabric 112 (e.g.,overlay network coupled with the fabric 112), etc. Engines 120 can becoupled with the fabric 112 via the leaf switches 104, for example.

While collectors 118 and engines 120 are shown as separate entities,this is simply a non-limiting example for illustration purposes, asother configurations are also contemplated herein. For example, any ofcollectors 118 and engines 120 can be part of a same or separate entity.Moreover, any of the collector, aggregation, and analytics functions canbe implemented by one entity (e.g., a collector 118 or engine 120) orseparately implemented by multiple entities (e.g., engines 120 and/orcollectors 118).

Each of the capturing agents 116 can use a respective address (e.g.,internet protocol (IP) address, port number, etc.) of their host to sendinformation to collectors 118 and/or any other destination. Collectors118 may also be associated with their respective addresses such as IPaddresses. Moreover, capturing agents 116 can periodically sendinformation about flows they observe to collectors 118. Capturing agents116 can be configured to report each and every flow they observe or asubset of flows they observe. For example, capturing agents 116 canreport every flow always, every flow within a period of time, every flowat one or more intervals, or a subset of flows during a period of timeor at one or more intervals.

Capturing agents 116 can report a list of flows that were active duringa period of time (e.g., between the current time and the time of thelast report). The consecutive periods of time of observance can berepresented as pre-defined or adjustable time series. The series can beadjusted to a specific level of granularity. Thus, the time periods canbe adjusted to control the level of details in statistics and can becustomized based on specific requirements or conditions, such assecurity, scalability, bandwidth, storage, etc. The time seriesinformation can also be implemented to focus on more important flows orcomponents (e.g., VMs) by varying the time intervals. The communicationchannel between a capturing agent and collector 118 can also create aflow in every reporting interval. Thus, the information transmitted orreported by capturing agents 116 can also include information about theflow created by the communication channel.

When referring to a capturing agent's host herein, the host can refer tothe physical device or component hosting the capturing agent (e.g.,server, networking device, ASIC, etc.), the virtualized environmenthosting the capturing agent (e.g., hypervisor, virtual machine, etc.),the operating system hosting the capturing agent (e.g., guest operatingsystem, host operating system, etc.), and/or system layer hosting thecapturing agent (e.g., hardware layer, operating system layer,hypervisor layer, virtual machine layer, etc.).

FIG. 2A illustrates a schematic diagram of an example capturing agentdeployment 200 in a server 106 _(A). Server 106 _(A) can execute andhost one or more VMs 110 _(A-N) (collectively “110”). VMs 110 can beconfigured to run workloads (e.g., applications, services, processes,functions, etc.) based on hardware resources 210 on server 106 _(A). VMs110 can run on guest operating systems 204 _(A-N) (collectively “204”)on a virtual operating platform provided by hypervisor 108 _(A). Each VM110 can run a respective guest operating system 204 which can be thesame or different as other guest operating systems 204 associated withother VMs 110 on server 106 _(A). Each of guest operating systems 204can execute one or more processes, which may in turn be programs,applications, modules, drivers, services, widgets, etc. Moreover, eachVM 110 can have one or more network addresses, such as an internetprotocol (IP) address. VMs 110 can thus communicate with hypervisor 108_(A), server 106 _(A), and/or any remote devices or networks using theone or more network addresses.

Hypervisor 108 _(A) (otherwise known as a virtual machine manager ormonitor) can be a layer of software, firmware, and/or hardware thatcreates and runs VMs 110. Guest operating systems 204 running on VMs 110can share virtualized hardware resources created by hypervisor 108 _(A).The virtualized hardware resources can provide the illusion of separatehardware components. Moreover, the virtualized hardware resources canperform as physical hardware components (e.g., memory, storage,processor, network interface, peripherals, etc.), and can be driven byhardware resources 210 on server 106 _(A). Hypervisor 108 _(A) can haveone or more network addresses, such as an internet protocol (IP)address, to communicate with other devices, components, or networks. Forexample, hypervisor 108 _(A) can have a dedicated IP address which itcan use to communicate with VMs 110, server 106 _(A), and/or any remotedevices or networks.

Hypervisor 108 _(A) can be assigned a network address, such as an IP,with a global scope. For example, hypervisor 108 _(A) can have an IPthat can be reached or seen by VMs 110 _(A-N) as well any other devicesin the network environment 100 illustrated in FIG. 1. On the other hand,VMs 110 can have a network address, such as an IP, with a local scope.For example, VM 110 _(A) can have an IP that is within a local networksegment where VM 110 _(A) resides and/or which may not be directlyreached or seen from other network segments in the network environment100.

Hardware resources 210 of server 106 _(A) can provide the underlyingphysical hardware that drive operations and functionalities provided byserver 106 _(A), hypervisor 108 _(A), and VMs 110. Hardware resources210 can include, for example, one or more memory resources, one or morestorage resources, one or more communication interfaces, one or moreprocessors, one or more circuit boards, one or more buses, one or moreextension cards, one or more power supplies, one or more antennas, oneor more peripheral components, etc. Additional examples of hardwareresources are described below with reference to FIGS. 10 and 11A-B.

Server 106 _(A) can also include one or more host operating systems (notshown). The number of host operating systems can vary by configuration.For example, some configurations can include a dual boot configurationthat allows server 106 _(A) to boot into one of multiple host operatingsystems. In other configurations, server 106 _(A) may run a single hostoperating system. Host operating systems can run on hardware resources210. In some cases, hypervisor 108 _(A) can run on, or utilize, a hostoperating system on server 106 _(A). Each of the host operating systemscan execute one or more processes, which may be programs, applications,modules, drivers, services, widgets, etc.

Server 106 _(A) can also have one or more network addresses, such as anIP address, to communicate with other devices, components, or networks.For example, server 106 _(A) can have an IP address assigned to acommunications interface from hardware resources 210, which it can useto communicate with VMs 110, hypervisor 108 _(A), leaf router 104 _(A)in FIG. 1, collectors 118 in FIG. 1, and/or any remote devices ornetworks.

VM capturing agents 202 _(A-N) (collectively “202”) can be deployed onone or more of VMs 110. VM capturing agents 202 can be data and packetinspection agents or sensors deployed on VMs 110 to capture packets,flows, processes, events, traffic, and/or any data flowing into, out of,or through VMs 110. VM capturing agents 202 can be configured to exportor report any data collected or captured by the capturing agents 202 toa remote entity, such as collectors 118, for example. VM capturingagents 202 can communicate or report such data using a network addressof the respective VMs 110 (e.g., VM IP address).

VM capturing agents 202 can capture and report any traffic (e.g.,packets, flows, etc.) sent, received, generated, and/or processed by VMs110. For example, capturing agents 202 can report every packet or flowof communication sent and received by VMs 110. Such communicationchannel between capturing agents 202 and collectors 108 creates a flowin every monitoring period or interval and the flow generated bycapturing agents 202 may be denoted as a control flow. Moreover, anycommunication sent or received by VMs 110, including data reported fromcapturing agents 202, can create a network flow. VM capturing agents 202can report such flows in the form of a control flow to a remote device,such as collectors 118 illustrated in FIG. 1.

VM capturing agents 202 can report each flow separately or aggregatedwith other flows. When reporting a flow via a control flow, VM capturingagents 202 can include a capturing agent identifier that identifiescapturing agents 202 as reporting the associated flow. VM capturingagents 202 can also include in the control flow a flow identifier, an IPaddress, a timestamp, metadata, a process ID, an OS username associatedwith the process ID, a host or environment descriptor (e.g., type ofsoftware bridge or virtual network card, type of host such as ahypervisor or VM, etc.), and any other information, as further describedbelow. In addition, capturing agents 202 can append the process and userinformation (i.e., which process and/or user is associated with aparticular flow) to the control flow. The additional information asidentified above can be applied to the control flow as labels.Alternatively, the additional information can be included as part of aheader, a trailer, or a payload.

VM capturing agents 202 can also report multiple flows as a set offlows. When reporting a set of flows, VM capturing agents 202 caninclude a flow identifier for the set of flows and/or a flow identifierfor each flow in the set of flows. VM capturing agents 202 can alsoinclude one or more timestamps and other information as previouslyexplained.

VM capturing agents 202 can run as a process, kernel module, or kerneldriver on guest operating systems 204 of VMs 110. VM capturing agents202 can thus monitor any traffic sent, received, or processed by VMs110, any processes running on guest operating systems 204, any users anduser activities on guest operating system 204, any workloads on VMs 110,etc.

Hypervisor capturing agent 206 can be deployed on hypervisor 108 _(A).Hypervisor capturing agent 206 can be a data inspection agent or sensordeployed on hypervisor 108 _(A) to capture traffic (e.g., packets,flows, etc.) and/or data flowing through hypervisor 108 _(A). Hypervisorcapturing agent 206 can be configured to export or report any datacollected or captured by hypervisor capturing agent 206 to a remoteentity, such as collectors 118, for example. Hypervisor capturing agent206 can communicate or report such data using a network address ofhypervisor 108 _(A), such as an IP address of hypervisor 108 _(A).

Because hypervisor 108 _(A) can see traffic and data originating fromVMs 110, hypervisor capturing agent 206 can also capture and report anydata (e.g., traffic data) associated with VMs 110. For example,hypervisor capturing agent 206 can report every packet or flow ofcommunication sent or received by VMs 110 and/or VM capturing agents202. Moreover, any communication sent or received by hypervisor 108_(A), including data reported from hypervisor capturing agent 206, cancreate a network flow. Hypervisor capturing agent 206 can report suchflows in the form of a control flow to a remote device, such ascollectors 118 illustrated in FIG. 1. Hypervisor capturing agent 206 canreport each flow separately and/or in combination with other flows ordata.

When reporting a flow, hypervisor capturing agent 206 can include acapturing agent identifier that identifies hypervisor capturing agent206 as reporting the flow. Hypervisor capturing agent 206 can alsoinclude in the control flow a flow identifier, an IP address, atimestamp, metadata, a process ID, and any other information, asexplained below. In addition, capturing agents 206 can append theprocess and user information (i.e., which process and/or user isassociated with a particular flow) to the control flow. The additionalinformation as identified above can be applied to the control flow aslabels. Alternatively, the additional information can be included aspart of a header, a trailer, or a payload.

Hypervisor capturing agent 206 can also report multiple flows as a setof flows. When reporting a set of flows, hypervisor capturing agent 206can include a flow identifier for the set of flows and/or a flowidentifier for each flow in the set of flows. Hypervisor capturing agent206 can also include one or more timestamps and other information aspreviously explained, such as process and user information.

As previously explained, any communication captured or reported by VMcapturing agents 202 can flow through hypervisor 108 _(A). Thus,hypervisor capturing agent 206 can observe and capture any flows orpackets reported by VM capturing agents 202, including any controlflows. Accordingly, hypervisor capturing agent 206 can also report anypackets or flows reported by VM capturing agents 202 and any controlflows generated by VM capturing agents 202. For example, VM capturingagent 202 _(A) on VM 1 (110 _(A)) captures flow 1 (“F1”) and reports F1to collector 118 on FIG. 1. Hypervisor capturing agent 206 on hypervisor108 _(A) can also see and capture F1, as F1 would traverse hypervisor108 _(A) when being sent or received by VM 1 (110 _(A)). Accordingly,hypervisor capturing agent 206 on hypervisor 108 _(A) can also report F1to collector 118. Thus, collector 118 can receive a report of F1 from VMcapturing agent 202 _(A) on VM 1 (110 _(A)) and another report of F1from hypervisor capturing agent 206 on hypervisor 108 _(A).

When reporting F, hypervisor capturing agent 206 can report F1 as amessage or report that is separate from the message or report of F1transmitted by VM capturing agent 202 _(A) on VM 1 (110 _(A)). However,hypervisor capturing agent 206 can also, or otherwise, report F1 as amessage or report that includes or appends the message or report of F1transmitted by VM capturing agent 202 _(A) on VM 1 (110 _(A)). In otherwords, hypervisor capturing agent 206 can report F1 as a separatemessage or report from VM capturing agent 202 _(A)'S message or reportof F1, and/or a same message or report that includes both a report of F1by hypervisor capturing agent 206 and the report of F1 by VM capturingagent 202 _(A) at VM 1 (110 _(A)). In this way, VM capturing agents 202at VMs 110 can report packets or flows received or sent by VMs 110, andhypervisor capturing agent 206 at hypervisor 108 _(A) can report packetsor flows received or sent by hypervisor 108 _(A), including any flows orpackets received or sent by VMs 110 and/or reported by VM capturingagents 202.

Hypervisor capturing agent 206 can run as a process, kernel module, orkernel driver on the host operating system associated with hypervisor108 _(A). Hypervisor capturing agent 206 can thus monitor any trafficsent and received by hypervisor 108 _(A), any processes associated withhypervisor 108 _(A), etc.

Server 106 _(A) can also have server capturing agent 208 running on it.Server capturing agent 208 can be a data inspection agent or sensordeployed on server 106 _(A) to capture data (e.g., packets, flows,traffic data, etc.) on server 106 _(A). Server capturing agent 208 canbe configured to export or report any data collected or captured byserver capturing agent 206 to a remote entity, such as collector 118,for example. Server capturing agent 208 can communicate or report suchdata using a network address of server 106 _(A), such as an IP addressof server 106 _(A).

Server capturing agent 208 can capture and report any packet or flow ofcommunication associated with server 106 _(A). For example, capturingagent 208 can report every packet or flow of communication sent orreceived by one or more communication interfaces of server 106 _(A).Moreover, any communication sent or received by server 106 _(A),including data reported from capturing agents 202 and 206, can create anetwork flow associated with server 106 _(A). Server capturing agent 208can report such flows in the form of a control flow to a remote device,such as collector 118 illustrated in FIG. 1. Server capturing agent 208can report each flow separately or in combination. When reporting aflow, server capturing agent 208 can include a capturing agentidentifier that identifies server capturing agent 208 as reporting theassociated flow. Server capturing agent 208 can also include in thecontrol flow a flow identifier, an IP address, a timestamp, metadata, aprocess ID, and any other information. In addition, capturing agent 208can append the process and user information (i.e., which process and/oruser is associated with a particular flow) to the control flow. Theadditional information as identified above can be applied to the controlflow as labels. Alternatively, the additional information can beincluded as part of a header, a trailer, or a payload.

Server capturing agent 208 can also report multiple flows as a set offlows. When reporting a set of flows, server capturing agent 208 caninclude a flow identifier for the set of flows and/or a flow identifierfor each flow in the set of flows. Server capturing agent 208 can alsoinclude one or more timestamps and other information as previouslyexplained.

Any communications captured or reported by capturing agents 202 and 206can flow through server 106 _(A). Thus, server capturing agent 208 canobserve or capture any flows or packets reported by capturing agents 202and 206. In other words, network data observed by capturing agents 202and 206 inside VMs 110 and hypervisor 108 _(A) can be a subset of thedata observed by server capturing agent 208 on server 106 _(A).Accordingly, server capturing agent 208 can report any packets or flowsreported by capturing agents 202 and 206 and any control flows generatedby capturing agents 202 and 206. For example, capturing agent 202 _(A)on VM 1 (110 _(A)) captures flow 1 (F1) and reports F1 to collector 118as illustrated on FIG. 1. Capturing agent 206 on hypervisor 108 _(A) canalso observe and capture F1, as F1 would traverse hypervisor 108 _(A)when being sent or received by VM 1 (110 _(A)). In addition, capturingagent 206 on server 106 _(A) can also see and capture F1, as F1 wouldtraverse server 106 _(A) when being sent or received by VM 1 (110 _(A))and hypervisor 108 _(A). Accordingly, capturing agent 208 can alsoreport F1 to collector 118. Thus, collector 118 can receive a report(i.e., control flow) regarding F1 from capturing agent 202 _(A) on VM 1(110 _(A)), capturing agent 206 on hypervisor 108 _(A), and capturingagent 208 on server 106 _(A).

When reporting F1, server capturing agent 208 can report F1 as a messageor report that is separate from any messages or reports of F1transmitted by capturing agent 202 _(A) on VM 1 (110 _(A)) or capturingagent 206 on hypervisor 108 _(A). However, server capturing agent 208can also, or otherwise, report F1 as a message or report that includesor appends the messages or reports or metadata of F1 transmitted bycapturing agent 202 _(A) on VM 1 (110 _(A)) and capturing agent 206 onhypervisor 108 _(A). In other words, server capturing agent 208 canreport F1 as a separate message or report from the messages or reportsof F1 from capturing agent 202 _(A) and capturing agent 206, and/or asame message or report that includes a report of F1 by capturing agent202 _(A), capturing agent 206, and capturing agent 208. In this way,capturing agents 202 at VMs 110 can report packets or flows received orsent by VMs 110, capturing agent 206 at hypervisor 108 _(A) can reportpackets or flows received or sent by hypervisor 108 _(A), including anyflows or packets received or sent by VMs 110 and reported by capturingagents 202, and capturing agent 208 at server 106 _(A) can reportpackets or flows received or sent by server 106 _(A), including anyflows or packets received or sent by VMs 110 and reported by capturingagents 202, and any flows or packets received or sent by hypervisor 108_(A) and reported by capturing agent 206.

Server capturing agent 208 can run as a process, kernel module, orkernel driver on the host operating system or a hardware component ofserver 106 _(A). Server capturing agent 208 can thus monitor any trafficsent and received by server 106 _(A), any processes associated withserver 106 _(A), etc.

In addition to network data, capturing agents 202, 206, and 208 cancapture additional information about the system or environment in whichthey reside. For example, capturing agents 202, 206, and 208 can capturedata or metadata of active or previously active processes of theirrespective system or environment, operating system user identifiers,metadata of files on their respective system or environment, timestamps,network addressing information, flow identifiers, capturing agentidentifiers, etc. Capturing agents 202, 206, and 208

Moreover, capturing agents 202, 206, 208 are not specific to anyoperating system environment, hypervisor environment, networkenvironment, or hardware environment. Thus, capturing agents 202, 206,and 208 can operate in any environment.

As previously explained, capturing agents 202, 206, and 208 can sendinformation about the network traffic they observe. This information canbe sent to one or more remote devices, such as one or more servers,collectors, engines, etc. Each capturing agent can be configured to sendrespective information using a network address, such as an IP address,and any other communication details, such as port number, to one or moredestination addresses or locations. Capturing agents 202, 206, and 208can send metadata about one or more flows, packets, communications,processes, events, etc.

Capturing agents 202, 206, and 208 can periodically report informationabout each flow or packet they observe. The information reported cancontain a list of flows or packets that were active during a period oftime (e.g., between the current time and the time at which the lastinformation was reported). The communication channel between thecapturing agent and the destination can create a flow in every interval.For example, the communication channel between capturing agent 208 andcollector 118 can create a control flow. Thus, the information reportedby a capturing agent can also contain information about this controlflow. For example, the information reported by capturing agent 208 tocollector 118 can include a list of flows or packets that were active athypervisor 108 _(A) during a period of time, as well as informationabout the communication channel between capturing agent 206 andcollector 118 used to report the information by capturing agent 206.

FIG. 2B illustrates a schematic diagram of example capturing agentdeployment 220 in an example network device. The network device isdescribed as leaf router 104 _(A), as illustrated in FIG. 1. However,this is for explanation purposes. The network device can be any othernetwork device, such as any other switch, router, etc.

In this example, leaf router 104 _(A) can include network resources 222,such as memory, storage, communication, processing, input, output, andother types of resources. Leaf router 104 _(A) can also includeoperating system environment 224. The operating system environment 224can include any operating system, such as a network operating system,embedded operating system, etc. Operating system environment 224 caninclude processes, functions, and applications for performingnetworking, routing, switching, forwarding, policy implementation,messaging, monitoring, and other types of operations. Leaf router 104_(A) can also include capturing agent 226. Capturing agent 226 can be anagent or sensor configured to capture network data, such as flows orpackets, sent received, or processed by leaf router 104 _(A). Capturingagent 226 can also be configured to capture other information, such asprocesses, statistics, users, alerts, status information, deviceinformation, etc. Moreover, capturing agent 226 can be configured toreport captured data to a remote device or network, such as collector118 shown in FIG. 1, for example. Capturing agent 226 can reportinformation using one or more network addresses associated with leafrouter 104 _(A) or collector 118. For example, capturing agent 226 canbe configured to report information using an IP assigned to an activecommunications interface on leaf router 104 _(A).

Leaf router 104 _(A) can be configured to route traffic to and fromother devices or networks, such as server 106 _(A). Accordingly,capturing agent 226 can also report data reported by other capturingagents on other devices. For example, leaf router 104 _(A) can beconfigured to route traffic sent and received by server 106 _(A) toother devices. Thus, data reported from capturing agents deployed onserver 106 _(A), such as VM and hypervisor capturing agents on server106 _(A), would also be observed by capturing agent 226 and can thus bereported by capturing agent 226 as data observed at leaf router 104_(A). Such report can be a control flow generated by capturing agent226. Data reported by the VM and hypervisor capturing agents on server106 _(A) can therefore be a subset of the data reported by capturingagent 226.

Capturing agent 226 can run as a process or component (e.g., firmware,module, hardware device, etc.) in leaf router 104 _(A). Moreover,capturing agent 226 can be installed on leaf router 104 _(A) as asoftware or firmware agent. In some configurations, leaf router 104 _(A)itself can act as capturing agent 226. Moreover, capturing agent 226 canrun within operating system 224 and/or separate from operating system224.

FIG. 2C illustrates a schematic diagram of example reporting system 240in an example capturing agent topology. The capturing agent topologyincludes capturing agents along a path from a virtualized environment(e.g., VM and hypervisor) to the fabric 112.

Leaf router 104 _(A) can route packets or traffic 242 between fabric 112and server 106 _(A), hypervisor 108 _(A), and VM 110 _(A). Packets ortraffic 242 between VM 110 _(A) and leaf router 104 _(A) can flowthrough hypervisor 108 _(A) and server 106 _(A). Packets or traffic 242between hypervisor 108 _(A) and leaf router 104 _(A) can flow throughserver 106 _(A). Finally, packets or traffic 242 between server 106 _(A)and leaf router 104 _(A) can flow directly to leaf router 104 _(A).However, in some cases, packets or traffic 242 between server 106 _(A)and leaf router 104 _(A) can flow through one or more interveningdevices or networks, such as a switch or a firewall.

Moreover, VM capturing agent 202 _(A) at VM 110 _(A), hypervisorcapturing agent 206 at hypervisor 108 _(A), network device capturingagent 226 at leaf router 104 _(A), and any server capturing agent atserver 106 _(A) (e.g., capturing agent running on host environment ofserver 106 _(A)) can send reports 244 (also referred to as controlflows) to collector 118 based on the packets or traffic 242 captured ateach respective capturing agent. Reports 244 from VM capturing agent 202_(A) to collectors 118 can flow through VM 110 _(A), hypervisor 108_(A), server 106 _(A), and leaf router 104 _(A). Reports 244 fromhypervisor capturing agent 206 to collectors 118 can flow throughhypervisor 108 _(A), server 106 _(A), and leaf router 104 _(A). Reports244 from any other server capturing agent at server 106 _(A) tocollectors 118 can flow through server 106 _(A) and leaf router 104_(A). Finally, reports 244 from network device capturing agent 226 tocollectors 118 can flow through leaf router 104 _(A). Although reports244 are depicted as being routed separately from traffic 242 in FIG. 2C,one of ordinary skill in the art will understand that reports 244 andtraffic 242 can be transmitted through the same communicationchannel(s).

Reports 244 can include any portion of packets or traffic 242 capturedat the respective capturing agents. Reports 244 can also include otherinformation, such as timestamps, process information, capturing agentidentifiers, flow identifiers, flow statistics, notifications, logs,user information, system information, etc. Some or all of thisinformation can be appended to reports 244 as one or more labels,metadata, or as part of the packet(s)' header, trailer, or payload. Forexample, if a user opens a browser on VM 110 _(A) and navigates toexamplewebsite.com, VM capturing agent 202 _(A) of VM 110 _(A) candetermine which user (i.e., operating system user) of VM 110 _(A) (e.g.,username “johndoe85”) and which process being executed on the operatingsystem of VM 110 _(A) (e.g., “chrome.exe”) were responsible for theparticular network flow to and from examplewebsite.com. Once suchinformation is determined, the information can be included in report 244as labels for example, and report 244 can be transmitted from VMcapturing agent 202 _(A) to collectors 118. Such additional informationcan help system 240 to gain insight into flow information at the processand user level, for instance. This information can be used for security,optimization, and determining structures and dependencies within system240.

In some examples, the reports 244 can include various statistics and/orusage information reported by the respective capturing agents. Forexample, the reports 244 can indicate an amount of traffic captured bythe respective capturing agent, which can include the amount of trafficsent, received, and generated by the capturing agent's host; a type oftraffic captured, such as video, audio, Web (e.g., HTTP or HTTPS),database queries, application traffic, etc.; a source and/or destinationof the traffic, such as a destination server or application, a sourcenetwork or device, a source or destination address or name (e.g., IPaddress, DNS name, FQDN, packet label, MAC address, VLAN, VNID, VxLAN,source or destination domain, etc.); a source and/or destination port(e.g., port 25, port 80, port 443, port 8080, port 22); a trafficprotocol; traffic metadata; etc. The reports 244 can also includeindications of traffic or usage patterns and information, such asfrequency of communications, intervals, type of requests, type ofresponses, triggering processes or events (e.g., causality), resourceusage, etc.

Each of the capturing agents 202 _(A), 206, 226 can include a respectiveunique capturing agent identifier on each of reports 244 it sends tocollectors 118, to allow collectors 118 to determine which capturingagent sent the report. Capturing agent identifiers in reports 244 canalso be used to determine which capturing agents reported what flows.Reports 244 can also include a flow identifier for each flow reportedand a timestamp identifying a time period when the traffic was capturedand/or reported. This information can then be used to determineanalytics information, such as a capturing agent placement and topology,traffic statistics, usage information, activity details, a mapping offlows to processes and users, current conditions, etc. Such additionalinsights gained can be useful for analyzing the data in reports 244, aswell as troubleshooting, security, visualization, configuration,planning, and management, and so forth.

As previously noted, the topology of the capturing agents can beascertained from the reports 244. To illustrate, a packet received by VM110 _(A) from fabric 112 can be captured and reported by VM capturingagent 202 _(A). Since the packet received by VM 110 _(A) will also flowthrough leaf router 104 _(A) and hypervisor 108 _(A), it can also becaptured and reported by hypervisor capturing agent 206 and networkdevice capturing agent 226. Thus, for a packet received by VM 110 _(A)from fabric 112, collectors 118 can receive a report of the packet fromVM capturing agent 202 _(A), hypervisor capturing agent 206, and networkdevice capturing agent 226.

Similarly, a packet sent by VM 110 _(A) to fabric 112 can be capturedand reported by VM capturing agent 202 _(A). Since the packet sent by VM110 _(A) will also flow through leaf router 104 _(A) and hypervisor 108_(A), it can also be captured and reported by hypervisor capturing agent206 and network device capturing agent 226. Thus, for a packet sent byVM 110 _(A) to fabric 112, collectors 118 can receive a report of thepacket from VM capturing agent 202 _(A), hypervisor capturing agent 206,and network device capturing agent 226.

On the other hand, a packet originating at, or destined to, hypervisor108 _(A), can be captured and reported by hypervisor capturing agent 206and network device capturing agent 226, but not VM capturing agent 202_(A), as such packet may not flow through VM 110 _(A). Moreover, apacket originating at, or destined to, leaf router 104 _(A), will becaptured and reported by network device capturing agent 226, but not VMcapturing agent 202 _(A), hypervisor capturing agent 206, or any othercapturing agent on server 106 _(A), as such packet may not flow throughVM 110 _(A), hypervisor 108 _(A), or server 106 _(A).

Reports 244 can be transmitted to collectors 118 periodically as newpackets or traffic 242 are captured by a capturing agent, or otherwisebased on a schedule, interval, or event, for example. Further, eachcapturing agent can send a single report or multiple reports tocollectors 118. For example, each of the capturing agents can beconfigured to send a report to one or more collectors 118 for everyflow, packet, message, communication, or network data received,transmitted, and/or generated by its respective host (e.g., VM 110 _(A),hypervisor 108 _(A), server 106 _(A), and leaf router 104 _(A)). Assuch, collectors 118 can receive a report of a same packet from multiplecapturing agents. In other examples, one or more capturing agents can beconfigured to send a report to collectors 118 for one or more flows,packets, messages, communications, network data, or subset(s) thereof,received, transmitted, and/or generated by the respective host during aperiod of time or interval.

Collectors 118 can include a primary collector and a secondarycollector. Each capturing agent can send the reports 244 to both theprimary collector and the secondary collector. This can provideredundancy to ensure that any disruption to a collector does not resultin a disruption in the collection or reporting of the reports 244.

FIG. 3 illustrates a schematic diagram of an example configuration 300for collecting capturing agent reports (i.e., control flows). Inconfiguration 300, traffic between fabric 112 and VM 110 _(A) isconfigured to flow through leaf router 104 _(A), server 106 _(A), andhypervisor 108 _(A). Moreover, traffic between fabric 112 and hypervisor108 _(A) is configured to flow through leaf router 104 _(A).

VM capturing agent 202 _(A) can be configured to report to collector 118traffic sent, received, or processed by VM 110 _(A). Hypervisorcapturing agent 206 can be configured to report to collectors 118traffic sent, received, or processed by hypervisor 108 _(A). Finally,network device capturing agent 226 can be configured to report tocollectors 118 traffic sent, received, or processed by leaf router 104_(A).

The collectors 118 can receive flow 302 from VM capturing agent 202_(A), flow 304 from hypervisor capturing agent 206, and flow 306 fromnetwork device capturing agent 226. Flow 302 can include flows capturedby VM capturing agent 202 _(A) at VM 110 _(A). Flow 304 can includeflows captured by hypervisor capturing agent 206 at hypervisor 108 _(A).Flows captured by hypervisor capturing agent 206 can also include flow302 captured by VM capturing agent 202 _(A), as traffic sent andreceived by VM 110 _(A) will be received and observed by hypervisor 108_(A) and captured by hypervisor capturing agent 206. Flow 306 caninclude flows captured by network device capturing agent 226 at leafrouter 104 _(A). Flows captured by network device capturing agent 226can also include flow 302 captured by VM capturing agent 202 _(A) andflow 304 captured by hypervisor capturing agent 206, as traffic sent andreceived by VM 110 _(A) and hypervisor 108 _(A) is routed through leafrouter 104 _(A) and can thus be captured by network device capturingagent 226.

Engine 120 can process the information, including any information aboutthe capturing agents (e.g., agent placement, agent environment, etc.)and/or the captured traffic (e.g., statistics), received from thecollector 118 to identify patterns, conditions, network or devicecharacteristics; log statistics or history details; aggregate and/orprocess the data; generate reports, timelines, alerts, graphical userinterfaces; detect errors, events, inconsistencies; troubleshootnetworks or devices; configure networks or devices; deploy services ordevices; reconfigure services, applications, devices, or networks; etc.

Collector 118 and/or engine 120 can map individual flows that traverseVM 110 _(A), hypervisor 108 _(A), and/or leaf router 104 _(A) to thespecific capturing agents at VM 110 _(A), hypervisor 108 _(A), and/orleaf router 104 _(A). For example, collector 118 and/or engine 120 candetermine that a particular flow that originated from VM 110 _(A) anddestined for fabric 112 was sent by VM 110 _(A) and such flow wasreported by VM capturing agent 202 _(A). Other information, such asprocess, user, timing, and/or other details may also be determined forthe various flows. For example, it may be determined that the same flowwas received by a process named Z on hypervisor 108 _(A) and forwardedto a process named Won leaf router 104 _(A) and also reported byhypervisor capturing agent 206.

While engine 120 is illustrated as a separate entity, otherconfigurations are also contemplated herein. For example, engine 120 canbe part of a centralized collector and/or a separate entity. Indeed,engine 120 can include one or more devices, applications, modules,databases, processing components, elements, etc.

FIG. 4A illustrates a schematic diagram of a multi-layer sharding scheme400. Groups of capturing agents 402A-C in the network can be mapped toshards 406A-C in a first layer of shards 404. For example, group 402Acan be mapped to shard 406A, group 402B can be mapped to shard 406B, andgroup 402C can be mapped to shard 406C. Capturing agents in a group willreport captured data to the shard they are assigned to. Thus, capturingagents in the group 402A of capturing agents will report captured datato shard 406A, the capturing agents in the group 402B of capturingagents will report captured data to shard 406B, and capturing agents inthe group 402C of capturing agents will report captured data to shard406C. Other configurations are also contemplated herein. For example, anagent in one group can be mapped to a different shard than one or moreagents in the same group.

The capturing agents can send their captured data to their mapped shardfor collection by any of the collectors in that specific shard. Forexample, the capturing agents in group 402A may send their captured datato shard 406A for collection by one or more of the collectors in shard406A without specifying which particular collector should receive thedata. However, in other examples, the capturing agents in the group 402Acan select one or more specific collectors from their mapped shard 406Ato receive their captured data. To illustrate, a capturing agent in thegroup 402A can select a collector in the shard 406A by hashing a flowkey associated with the flow the capturing agent intends to report tothat collector. Here, the specific collector from the shard 406A can beassigned to a hash value which corresponds to the value obtained whenhashing the flow key of the particular flow. Thus, all data reported bythat capturing agent for that flow will be sent to that particularcollector in the shard 406A.

The grouping of capturing agents and mapping of the groups of capturingagents 402A-C to shards of collectors 406A-C can help scale thereporting and collecting of data captured by the capturing agents 116 inthe network. However, since multiple capturing agents can be involved inthe same communication and the capturing agents involved in anycommunication can vary, some communications may involve capturing agentsthat are assigned to different shards 406A-C in the first layer ofshards 404. In these scenarios, each of the capturing agents may sendtheir captured data for a particular flow to different collectors.Accordingly, each collector will only receive a portion of that flow.

For example, assume a communication associated with a flow involvescapturing agent A in group 402A and capturing agent B in group 402A.Here, capturing agent 402A is mapped to shard 406A and capturing agent Bis also mapped to shard 406A. If both capturing agents A and B sendtheir captured portions of the flow to the same collector in shard 406A,then the receiving collector in shard 406A will receive the entireportion of the flow, including both ends of the communication.

However, assume a communication associated with a flow involvescapturing agent 4 (e.g., from agents 1-100) in group 402A and capturingagent 101 (e.g., from agents 101-1000) in group 402B. Here, capturingagent group 402A is mapped to shard 406A and capturing agent group 402Bis mapped to shard 406B. Thus, capturing agent 4 in group 402A may sendits portion of the flow to a collector (e.g., collector 4) in shard 406Awhile capturing agent 101 in group 402B may send its portion of the flowto a collector (e.g., collector 11) in shard 406B. Accordingly, each ofthe collectors (i.e., collector 4 and collector 11) will receive only aportion of the flow and thus will not have the entire portion of theflow from both ends of the communication (i.e., capturing agents 4 and101). This segmentation of the data may make it difficult to collect,analyze, and/or aggregate all of the data for a particular flow. Thescheme 400 can resolve this issue by creating a second layer of shards408 to unify, aggregate, and/or combine all portions of a flow that hasbeen sent to different collectors in the first layer 404.

The second layer 408 can include shards 410A-C containing one or morecollectors from the collectors 118. The collectors in the shards 410A-Ccan be mapped to flows according to respective mappings 412A-C thatensure that all portions of a flow received by different collectors inthe first layer 404 will be sent from the different collectors in thefirst layer 404 to the same collector in the second layer 408. Eachcollector in shards 410A-C from the second layer 408 can be assigned arespective flow key and hash. The collectors in shards 406A-C can thendetermine which collector from shards 410A-C in the second layer 408 tosend a received flow to by hashing the flow key of that flow. The resultof hashing the flow key of that flow should match the value of therespective flow key and hash assigned to a particular collector in theshards 410A-C in the second layer 408. This can ensure that all portionsof that flow will be reported to the same collector in the shards 410A-Cin the second layer 408. Accordingly, all ends of a communicationassociated with a flow can be maintained together or aggregated even ifvarious portions of the flow are initially reported to differentcollectors in the first layer 404.

When a collector receives a flow from a capturing agent, it candetermine if it has received the entire portion of the flow (e.g., everyend of a communication associated with the flow). In a flow associatedwith a communication involving multiple capturing agents, the collectorcan determine if it received both ends of the flow (e.g., the portion ofthe flow captured by both capturing agents involved in thecommunication). For example, the collector can analyze the flow and/orits contents (e.g., packet headers, flow of communications, type ofcommunications, number of communications, etc.), and determine that thecommunication associated with a flow involved multiple parties. Toillustrate, the flow may include a source address and a destinationaddress which would indicate that at least two parties were involved inthe communication. As another example, the flow may include a type ofmessage or response, such as a SYN or ACK message, which suggests thatanother message or response should be expected for that flow (e.g., ifan ACK is included in the flow, one could expect a SYN message shouldalso be part of the flow as part of a handshake). As yet anotherexample, a flow may include identifiers, such as session or sequenceidentifiers, that may suggest that the flow should include X number ofpackets or messages. Thus, if the collector has obtained less than thatnumber, it can infer that it has not received the entire portion of thecommunication.

As noted above, if the collector has not received the entire portion ofthe flow (e.g., both ends of the communication of the flow or allpackets in a flow), it can infer that the other capturing agent isassigned/mapped to a different collector. This can trigger the collectorto send the flow it received from the particular capturing agent mappedto that collector to a different collector on the second layer 408. Theother capturing agent involved in the flow may similarly determine thatit has not received the entire portion of the flow, and consequentlysend its received portion to the same collector on the second layer 408.Accordingly, the collector from the second layer 408 will ultimatelyreceive every portion of the flow.

FIG. 4B illustrates a schematic diagram of a system 450 for hierarchicalsharding collectors, sensors, and flows in accordance with variousexample embodiments. Capturing agents 116 _(A-B) on VM 110 _(A) and VM110 _(B) can be mapped to shard 406A in the first layer 404. In thisexample, the capturing agent 116 _(A) on VM 110 _(A) can be mapped tocollector 2 in shard 406A from the first layer of shards 404, and thecapturing agent 116 _(B) on VM 110 _(B) can be mapped to collector 10 inshard 406A. Thus, the capturing agents 116 _(A-B) on VM 110 _(A) and VM110 _(B) can be configured to report their captured data to differentcollectors. This means that for communications involving both capturingagents, the respective flow data captured by the capturing agents willbe reported to different collectors, which can cause the flow data to bedivided between different collectors.

For example, assume flow 452 involving capturing agents on both VM 110_(A) and VM 110 _(B) includes a first portion (P1) and a second portion(P2). Further, assume that the capturing agent 116 _(A) on VM 110 _(A)is mapped to collector 2 and the capturing agent 116 _(B) on VM 1110_(B) is mapped to collector 10. In this example, the capturing agent 116_(A) on VM 110 _(A) may report the first portion (P1) 454 of the flow452 to collector 2, and the capturing agent 116 _(B) on VM 1110 _(B) mayreport the second portion (P2) 456 of the flow 452 to collector 10.Thus, collectors 2 and 10 from shard 406A will each receive only part ofthe flow 452, namely flows 454, 456. The reported flow 452 willtherefore be divided between collectors 2 and 10 from shard 406A.

Collectors 2 and 10 can thus analyze their respective portions of theflow 452 and determine that they did not receive the entire portion ofthe flow 452. For example, collector 2 from shard 406A can determinethat it has only received a first portion (P1) of the flow 452 and hasnot received another portion of the flow 452, namely, the second portion(P2), and vice versa. Collectors 2 and 10 from shard 406A can thusdetermine that they have collected some portion of the flow 452 but aremissing at least one other portion of the flow 452.

Collectors 2 and 10 from shard 406A can make this determination invarious ways and based on various factors. For example, collector 2 cananalyze the first portion (P1) of the flow 452 it has received anddetermine that it corresponds to only one end of the communicationassociated with the flow 452, and infer that it is missing at least aportion because it has not received any other end of the communication.As another example, collector 2 can determine that it has only receiveda portion of the flow corresponding to an incoming or received portionof the communication but does not have the portion corresponding to theoutgoing or transmitted portion of the communication. The collector 2can analyze the data it has received to determine whether other portionsof the flow 452 may be missing. For example, the collector 2 may analyzecharacteristics and/or statistics of the flow 452, such as number ofreceived or transmitted packets reported in the data received by thecollector 2, the destination address and/or port in the reportedpacket(s), source address and/or port in the reported packet(s), type ofcommunication associated with the reported packets (e.g., request and/orreply, SYN packet and/or ACK packet, etc.), number of nodes involved inthe communication versus number of nodes associated with the reportedpacket(s), etc.

When each of the collectors 2 and 10 from shard 406A determines that ithas not received the entire portion of the flow 452, it can forwardtheir received portion to a collector (e.g., collector 2) in shard 410Afrom the second layer 408 assigned to that particular flow. For example,collectors 2 and 10 from shard 406A in the first layer 404 can determinethat they each did not receive the entire portion of the flow 452, andforward their portion of the flow 452 to collector 2 in shard 410A fromthe second layer of shards 408. Collector 2 in shard 410A can be theparticular collector in the second layer 408 that is mapped to the flow452 (e.g., is assigned the flow key and hash of flow 452).

For example, the various collectors (e.g., collectors 1-10) in eachshard on the second layer 408 can be designated one or more particularflows, which they will be responsible for collecting and/or aggregatingfrom one or more collectors in the first layer 404. Collectors in thesecond layer 408 can be mapped to flows based on, for example, flowidentifiers, collector identifiers, hash values computed for the flows,etc. To illustrate, collector 2 from shard 410A in the second layer 408can be assigned to specific hash values computed for one or moreparticular flows. Thus, any flow that hashes to that hash value assignedto collector 2 will be forwarded to collector 2 from a receivingcollector in the first layer 404. This can ensure that all portions of aflow map to the same collector in the second layer 408.

Thus, in the previous example, collector 2 in shard 410A from the secondlayer 408 can receive the first portion (P1) of the flow 452 (i.e., flow454) from collector 2 in shard 406A on the first layer 404 and thesecond portion (P2) of the flow 452 from collector 10 (i.e., flow 456)in shard 406A on the first layer 404. Collector 2 in shard 410A from thesecond layer 408 can then aggregate the first portion (P1) and thesecond portion (P2) to obtain the entire flow 452. Any additionalportions of the flow 452 received by a collector in the first layer 404will also map to collector 2 in shard 410A on the second layer 408 and,therefore, will be forwarded to collector 2 in the second layer 408. Thecollector 2 in the second layer 408 can thus collect and/or aggregateall portions of the flow 452 from all collectors in the first layer 404that received a portion of the flow 452.

FIG. 5 illustrates a listing 500 of example fields on a capturing agentreport. The listing 500 can include one or more fields, such as:

Flow identifier (e.g., unique identifier associated with the flow).

Capturing agent identifier (e.g., data uniquely identifying reportingcapturing agent).

Timestamp (e.g., time of event, report, etc.).

Interval (e.g., time between current report and previous report,interval between flows or packets, interval between events, etc.).

Duration (e.g., duration of event, duration of communication, durationof flow, duration of report, etc.).

Flow direction (e.g., egress flow, ingress flow, etc.).

Application identifier (e.g., identifier of application associated withflow, process, event, or data).

Port (e.g., source port, destination port, layer 4 port, etc.).

Destination address (e.g., interface address associated withdestination, IP address, domain name, network address, hardware address,virtual address, physical address, etc.).

Source address (e.g., interface address associated with source, IPaddress, domain name, network address, hardware address, virtualaddress, physical address, etc.).

Interface (e.g., interface address, interface information, etc.).

Protocol (e.g., layer 4 protocol, layer 3 protocol, etc.).

Event (e.g., description of event, event identifier, etc.).

Flag (e.g., layer 3 flag, flag options, etc.).

Tag (e.g., virtual local area network tag, etc.).

Process (e.g., process identifier, etc.).

User (e.g., OS username, etc.).

Bytes (e.g., flow size, packet size, transmission size, etc.).

Sensor Type (e.g., the type of virtualized environment hosting thecapturing agent, such as hypervisor or VM; the type of virtual networkdevice, such as VNIC, LINUX bridge, OVS, software switch, etc.).

The listing 500 includes a non-limiting example of fields in a report.Other fields and data items are also contemplated herein, such ashandshake information, system information, network address associatedwith capturing agent or host, operating system environment information,network data or statistics, process statistics, system statistics, etc.The order in which these fields are illustrated is also exemplary andcan be rearranged in any other way. One or more of these fields can bepart of a header, a trailer, or a payload of in one or more packets.Moreover, one or more of these fields can be applied to the one or morepackets as labels. Each of the fields can include data, metadata, and/orany other information relevant to the fields.

Having disclosed some basic system components and concepts, thedisclosure now turns to the exemplary method embodiments shown in FIG.6. For the sake of clarity, the method is described with reference toFIGS. 1 and 4A-B. However, the example methods can be practiced by anysoftware or hardware components, devices, etc. heretofore disclosed. Thesteps outlined herein are exemplary and can be implemented in anycombination thereof in any order, including combinations that exclude,add, or modify certain steps.

At step 600, a first layer of shards 404 can be created containingrespective groups 406A-C of collectors. At step 602, a second layer ofshards 408 can be created containing respective groups 410A-C ofcollectors.

At step 604, capturing agents 116 deployed throughout a networkenvironment 100 can be assigned to respective shards 406A-C from thefirst layer 404. In some examples, the capturing agents 116 can also beassigned or map to specific collectors within the respective shards406A-C. Capturing agents 116 may be mapped to specific collectors basedon the captured flow they intend to report. For example, the capturingagents 116 may select a collector to send a flow to by hashing the flowor identifying a unique identifier for the flow. The collectors in therespective shards 406A-C can be assigned specific flows based on a hashvalue of the flow, a unique identifier of the flow, etc. Thus, acapturing agent can simply send a captured flow to a collector in thefirst layer 404 that is assigned to the hash value, unique ID, etc., ofthat particular flow.

In some cases, a capturing agent can be mapped to the same shard and/orcollector for all flows. For example, capturing agent A may be mapped tocollector X in shard 406A for all flows reported by capturing agent A.This assignment can be based on one or more factors, such as unique IDof the capturing agent and/or collector, the network address of thecapturing agent and/or collector, location of the capturing agent and/orcollector (e.g., physical location, logical location, geographiclocation, subnet or network segment, etc.), media access control (MAC)address of the collector and/or host associated with the capturingagent, etc.

In other cases, a capturing agent can be mapped to different shardsand/or collectors based on specific flows. For example, a capturingagent can be mapped to a shard and/or collector for each specific flow.Thus, the shard and/or collector mapped to the capturing agent may ormay not differ for different flows. As previously noted, collectors canbe assigned to specific flows based on one or more factors, such as hashvalue, unique ID, etc. Thus, the capturing agent can be mapped to aspecific collector for a flow and, in some cases, the capturing agentmay be mapped to a different collector for a different flow if thedifferent flow is assigned to a different collector.

At step 606, a collector (e.g., collector 2) in the first layer 404 canreceive a first portion 454 of a flow 452 from a first capturing agent(e.g., capturing agent 116 _(A) at VM 110 _(A)). At step 608, thecollector can determine that a second portion 456 of the flow 452 wasnot received by the collector. At step 610, the collector can then sendthe first portion 454 of the flow 452 to a collector (e.g., collector 2in shard 410A) in the second layer 408.

At step 612, another collector (e.g., collector 10 in shard 406A) in thefirst layer 404 can receive the second portion 456 of the flow 452 froma second capturing agent (e.g., capturing agent 116 _(B) at VM 110_(B)). At step 614, that collector can determine that the first portion454 of the flow 452 was not received by the collector. At step 616, thecollector can then send the second portion 456 of the flow 452 to thesame collector (e.g., collector 2 in shard 410A) in the second layer 408that received the first portion 454 of the flow 452.

At step 618, collector in the second layer 408 can determine that thefirst portion 454 and the second portion 456 are part of the same flow452. At step 620, the collector in the second layer 408 can combineand/or aggregate the first portion 454 and the second portion 456 toyield an aggregated network flow. The aggregated network flow can be thenetwork flow 452.

The disclosure now turns to the example network device and systemillustrated in FIGS. 7 and 8A-B.

FIG. 7 illustrates an example network device 700 according to someembodiments. Network device 700 includes a master central processingunit (CPU) 704, interfaces 702, and a bus 710 (e.g., a PCI bus). Whenacting under the control of appropriate software or firmware, the CPU704 is responsible for executing packet management, error detection,and/or routing functions. The CPU 704 preferably accomplishes all thesefunctions under the control of software including an operating systemand any appropriate applications software. CPU 704 may include one ormore processors 708 such as a processor from the Motorola family ofmicroprocessors or the MIPS family of microprocessors. In an alternativeembodiment, processor 708 is specially designed hardware for controllingthe operations of network device 700. In a specific embodiment, a memory706 (such as non-volatile RAM, ROM, TCAM, etc.) also forms part of CPU704. However, there are many different ways in which memory could becoupled to the system.

The interfaces 702 are typically provided as interface cards (sometimesreferred to as “line cards”). Generally, they control the sending andreceiving of data packets over the network and sometimes support otherperipherals used with the network device 700. Among the interfaces thatmay be provided are Ethernet interfaces, frame relay interfaces, cableinterfaces, DSL interfaces, token ring interfaces, and the like. Inaddition, various very high-speed interfaces may be provided such asfast token ring interfaces, wireless interfaces, Ethernet interfaces,Gigabit Ethernet interfaces, ATM interfaces, HSSI interfaces, POSinterfaces, FDDI interfaces and the like. Generally, these interfacesmay include ports appropriate for communication with the appropriatemedia. In some cases, they may also include an independent processorand, in some instances, volatile RAM. The independent processors maycontrol such communications intensive tasks as packet switching, mediacontrol and management. By providing separate processors for thecommunications intensive tasks, these interfaces allow the mastermicroprocessor 708 to efficiently perform routing computations, networkdiagnostics, security functions, etc.

Although the system shown in FIG. 7 is one specific network device ofthe present invention, it is by no means the only network devicearchitecture on which the present invention can be implemented. Forexample, an architecture having a single processor that handlescommunications as well as routing computations, etc. is often used.Further, other types of interfaces and media could also be used with thenetwork device. Moreover, network device can have various configurationsin different embodiments. For example, the network device 700 caninclude a Layer 2 and/or Layer 3 switch, a router, a bridge, a gateway,a traffic management or filtering system, etc. Further, the networkdevice 700 can include hardware and/or software/virtual networkingelements, such as an ASIC (application-specific integrated circuit), avirtual network interface, a virtual switch (e.g., vSwitch), etc.

Regardless of the network device's configuration, it may employ one ormore memories or memory modules (including memory 706) configured tostore program instructions for the general-purpose network operationsand mechanisms for roaming, route optimization and routing functionsdescribed herein. The program instructions may control the operation ofan operating system and/or one or more applications, for example. Thememory or memories may also be configured to store tables such asmobility binding, registration, and association tables, etc.

FIG. 8A and FIG. 8B illustrate example system embodiments. The moreappropriate embodiment will be apparent to those of ordinary skill inthe art when practicing the present technology. Persons of ordinaryskill in the art will also readily appreciate that other systemembodiments are possible.

FIG. 8A illustrates a conventional system bus computing systemarchitecture 800 wherein the components of the system are in electricalcommunication with each other using a bus 805. Exemplary system 800includes a processing unit (CPU or processor) 810 and a system bus 805that couples various system components including the system memory 815,such as read only memory (ROM) 820 and random access memory (RAM) 825,to the processor 810. The system 800 can include a cache of high-speedmemory connected directly with, in close proximity to, or integrated aspart of the processor 810. The system 800 can copy data from the memory815 and/or the storage device 830 to the cache 812 for quick access bythe processor 810. In this way, the cache can provide a performanceboost that avoids processor 810 delays while waiting for data. These andother modules can control or be configured to control the processor 810to perform various actions. Other system memory 815 may be available foruse as well. The memory 815 can include multiple different types ofmemory with different performance characteristics. The processor 810 caninclude any general purpose processor and a hardware module or softwaremodule, such as module 1 832, module 2 834, and module 3 836 stored instorage device 830, configured to control the processor 810 as well as aspecial-purpose processor where software instructions are incorporatedinto the actual processor design. The processor 810 may essentially be acompletely self-contained computing system, containing multiple cores orprocessors, a bus, memory controller, cache, etc. A multi-core processormay be symmetric or asymmetric.

To enable user interaction with the computing device 800, an inputdevice 845 can represent any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 835 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems can enable a user to provide multiple types of input tocommunicate with the computing device 800. The communications interface840 can generally govern and manage the user input and system output.There is no restriction on operating on any particular hardwarearrangement and therefore the basic features here may easily besubstituted for improved hardware or firmware arrangements as they aredeveloped.

Storage device 830 is a non-volatile memory and can be a hard disk orother types of computer readable media which can store data that areaccessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs) 825, read only memory (ROM) 820, andhybrids thereof.

The storage device 830 can include software modules 832, 834, 836 forcontrolling the processor 810. Other hardware or software modules arecontemplated. The storage device 830 can be connected to the system bus805. In one aspect, a hardware module that performs a particularfunction can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as the processor 810, bus 805, display 835, and soforth, to carry out the function.

FIG. 8B illustrates an example computer system 850 having a chipsetarchitecture that can be used in executing the described method andgenerating and displaying a graphical user interface (GUI). Computersystem 850 is an example of computer hardware, software, and firmwarethat can be used to implement the disclosed technology. System 850 caninclude a processor 855, representative of any number of physicallyand/or logically distinct resources capable of executing software,firmware, and hardware configured to perform identified computations.Processor 855 can communicate with a chipset 860 that can control inputto and output from processor 855. In this example, chipset 860 outputsinformation to output device 865, such as a display, and can read andwrite information to storage device 870, which can include magneticmedia, and solid state media, for example. Chipset 860 can also readdata from and write data to RAM 875. A bridge 880 for interfacing with avariety of user interface components 885 can be provided for interfacingwith chipset 860. Such user interface components 885 can include akeyboard, a microphone, touch detection and processing circuitry, apointing device, such as a mouse, and so on. In general, inputs tosystem 850 can come from any of a variety of sources, machine generatedand/or human generated.

Chipset 860 can also interface with one or more communication interfaces890 that can have different physical interfaces. Such communicationinterfaces can include interfaces for wired and wireless local areanetworks, for broadband wireless networks, as well as personal areanetworks. Some applications of the methods for generating, displaying,and using the GUI disclosed herein can include receiving ordereddatasets over the physical interface or be generated by the machineitself by processor 855 analyzing data stored in storage 870 or 875.Further, the machine can receive inputs from a user via user interfacecomponents 885 and execute appropriate functions, such as browsingfunctions by interpreting these inputs using processor 855.

It can be appreciated that example systems 800 and 850 can have morethan one processor 810 or be part of a group or cluster of computingdevices networked together to provide greater processing capability.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

In some embodiments the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims.

It should be understood that features or configurations herein withreference to one embodiment or example can be implemented in, orcombined with, other embodiments or examples herein. That is, terms suchas “embodiment”, “variation”, “aspect”, “example”, “configuration”,“implementation”, “case”, and any other terms which may connote anembodiment, as used herein to describe specific features orconfigurations, are not intended to limit any of the associated featuresor configurations to a specific or separate embodiment or embodiments,and should not be interpreted to suggest that such features orconfigurations cannot be combined with features or configurationsdescribed with reference to other embodiments, variations, aspects,examples, configurations, implementations, cases, and so forth. In otherwords, features described herein with reference to a specific example(e.g., embodiment, variation, aspect, configuration, implementation,case, etc.) can be combined with features described with reference toanother example. Precisely, one of ordinary skill in the art willreadily recognize that the various embodiments or examples describedherein, and their associated features, can be combined with each other.

A phrase such as an “aspect” does not imply that such aspect isessential to the subject technology or that such aspect applies to allconfigurations of the subject technology. A disclosure relating to anaspect may apply to all configurations, or one or more configurations. Aphrase such as an aspect may refer to one or more aspects and viceversa. A phrase such as a “configuration” does not imply that suchconfiguration is essential to the subject technology or that suchconfiguration applies to all configurations of the subject technology. Adisclosure relating to a configuration may apply to all configurations,or one or more configurations. A phrase such as a configuration mayrefer to one or more configurations and vice versa. The word “exemplary”is used herein to mean “serving as an example or illustration.” Anyaspect or design described herein as “exemplary” is not necessarily tobe construed as preferred or advantageous over other aspects or designs.

Moreover, claim language reciting “at least one of” a set indicates thatone member of the set or multiple members of the set satisfy the claim.For example, claim language reciting “at least one of A, B, and C” or“at least one of A, B, or C” both mean A alone, B alone, C alone, A andB together, A and C together, B and C together, or A, B and C together.

What is claimed is:
 1. A method for recombining a network flow, themethod comprising: assigning a plurality of capturing agents deployedthroughout a network to respective shards, each of the plurality ofcapturing agents being configured to capture network activity associatedwith a respective host and report the network activity to one or morecollectors in the respective shards, wherein each of the respectiveshards comprises a number of assigned collectors; receiving, by a firstcollector, a first portion of the network flow; receiving, at a secondcollector, a second portion of the network flow from a third collectorthat received the second portion of the network flow but not the firstportion of the network flow; determining, by the first collector, thatthe second portion of the network flow was not received at the firstcollector; in response to determining the second portion was notreceived, sending, by the first collector, the first portion of thenetwork flow to the second collector; and combining, by the secondcollector, the first portion of the network flow and the second portionof the network flow; wherein the second collector is part of a secondshard from the respective shards, and wherein the second collector isassigned a flow key and hash that corresponds to the network flow;wherein the second collector is selected to receive the first portionand the second portion of the network flow from a plurality of othercollectors based on the flow key and hash corresponding to the networkflow.
 2. The method of claim 1, wherein the first portion of the networkflow is transmitted by a first capturing agent to a first shard from therespective shards, wherein the first collector is part of the firstshard.
 3. The method of claim 1, wherein the first collector is mappedto a respective shard from a first layer of shards, each of therespective shards comprising a selected group of collectors, and whereinthe second collector is mapped to a shard from a second layer of shards.4. A non-transitory computer-readable storage medium storinginstructions to recombine a network flow, which when executed by atleast one processor cause the at least one processor to performoperations comprising: assigning a plurality of capturing agentsdeployed throughout a network to respective shards, each of theplurality of capturing agents being configured to capture networkactivity associated with a respective host and report the networkactivity to one or more collectors in the respective shards, whereineach of the respective shards comprises a number of assigned collectors;receiving, by a first collector, a first portion of the network flow;receiving, at a second collector, a second portion of the network flowfrom a third collector that received the second portion of the networkflow but not the first portion of the network flow; determining, by thefirst collector, that the second portion of the network flow was notreceived at the first collector; in response to determining the secondportion was not received, sending, by the first collector, the firstportion of the network flow to the second collector; and combining, bythe second collector, the first portion of the network flow and thesecond portion of the network flow; wherein the second collector is partof a second shard from the respective shards, and wherein the secondcollector is assigned a flow key and hash that corresponds to thenetwork flow; wherein the second collector is selected to receive thefirst portion and the second portion of the network flow from aplurality of other collectors based on the flow key and hashcorresponding to the network flow.
 5. The non-transitorycomputer-readable storage medium of claim 4, wherein the first portionof the network flow is transmitted by a first capturing agent to a firstshard from the respective shards, wherein the first collector is part ofthe first shard.
 6. The non-transitory computer-readable storage mediumof claim 4, wherein the first collector is mapped to a respective shardfrom a first layer of shards, each of the respective shards comprising aselected group of collectors, and wherein the second collector is mappedto a shard from a second layer of shards.
 7. A system that recombines anetwork flow, the system comprising: at least one processor; and atleast one non-transitory computer-readable storage medium having storedtherein instructions, which when executed by the at least one processor,causes the at least one processor to perform operations comprising:assigning a plurality of capturing agents deployed throughout a networkto respective shards, each of the plurality of capturing agents beingconfigured to capture network activity associated with a respective hostand report the network activity to one or more collectors in therespective shards, wherein each of the respective shards comprises anumber of assigned collectors; receiving, by a first collector, a firstportion of the network flow; receiving, at a second collector, a secondportion of the network flow from a third collector that received thesecond portion of the network flow but not the first portion of thenetwork flow; determining, by the first collector, that the secondportion of the network flow was not received at the first collector; inresponse to determining the second portion was not received, sending, bythe first collector, the first portion of the network flow to the secondcollector; and combining, by the second collector, the first portion ofthe network flow and the second portion of the network flow; wherein thesecond collector is part of a second shard from the respective shards,and wherein the second collector is assigned a flow key and hash thatcorresponds to the network flow; wherein the second collector isselected to receive the first portion and the second portion of thenetwork flow from a plurality of other collectors based on the flow keyand hash corresponding to the network flow.
 8. The system of claim 7,wherein the first portion of the network flow is transmitted by a firstcapturing agent to a first shard from the respective shards, wherein thefirst collector is part of the first shard.
 9. The system of claim 7,wherein the first collector is mapped to a respective shard from a firstlayer of shards, each of the respective shards comprising a selectedgroup of collectors, and wherein the second collector is mapped to ashard from a second layer of shards.